Semiautomated Device for Batch Extraction of Metabolites from Tissue Samples

ABSTRACT: Metabolomics has become a mainstream analytical strategy for investigating metabolism. The quality of data derived from these studies is proportional to the consistency of the sample preparation. Although considerable research has been devoted to finding optimal extraction protocols, most of the established methods require extensive sample handling. Manual sample preparation can be highly effective in the hands of skilled technicians, but an automated tool for purifying metabolites from complex biological tissues would be of obvious utility to the field. Here, we introduce the semiautomated metabolite batch extraction device (SAMBED), a new tool designed to simplify metabolomics sample preparation. We discuss SAMBED’s design and show that SAMBED-based extractions are of comparable quality to extracts produced through traditional methods (13 % mean coefficient of variation from SAMBED versus 16 % from manual extractions). Moreover, we show that aqueous SAMBED-based methods ca

Probabilistic Interaction Network of Evidence Algorithm and its Application to Complete Labeling of Peak Lists from Protein NMR Spectroscopy

The process of assigning a finite set of tags or labels to a collection of observations, subject to side conditions, is notable for its computational complexity. This labeling paradigm is of theoretical and practical relevance to a wide range of biological applications, including the analysis of data from DNA microarrays, metabolomics experiments, and biomolecular nuclear magnetic resonance (NMR) spectroscopy. We present a novel algorithm, called Probabilistic Interaction Network of Evidence (PINE), that achieves robust, unsupervised probabilistic labeling of data. The computational core of PINE uses estimates of evidence derived from empirical distributions of previously observed data, along with consistency measures, to drive a fictitious system M with Hamiltonian H to a quasi-stationary state that produces probabilistic label assignments for relevant subsets of the data. We demonstrate the successful application of PINE to a key task in protein NMR spectroscopy: that of converting peak lists extracted from various NMR experiments into assignments associated with probabilities for their correctness. This application, called PINE-NMR, is available from a freely accessible computer server (http://pine.nmrfam.wisc.edu). The PINE-NMR server accepts as input the sequence of the protein plus user-specified combinations of data corresponding to an extensive list of NMR experiments; it provides as output a probabilistic assignment of NMR signals (chemical shifts) to sequence-specific backbone and aliphatic side chain atoms plus a probabilistic determination of the protein secondary structure. PINE-NMR can accommodate prior information about assignments or stable isotope labeling schemes. As part of the analysis, PINE-NMR identifies, verifies, and rectifies problems related to chemical shift referencing or erroneous input data. PINE-NMR achieves robust and consistent results that have been shown to be effective in subsequent steps of NMR structure determination

SYNTHESIS OF MODEL-BASED CONTROLLERS FOR AN AUTOTHERMAL REACTOR

Model-based controllers for a bench scale autothermal tubular packed-bed reactor have been formulated using the Internal Model Control (IMC) approach. The Structural Dominance Analysis technique has been used in developing the reduced-order models. Controller performance at robust and sensitive steady states have been assessed through simulations and experiments. Both PI and model-based controllers can regulate reactor operation at robust steady states, but only third order IMC controllers are able to regulate reactor operation at the sensitive steady state.Endnote format citatio

DESIGN OF RESILIENT CONTROLLABLE CHEMICAL PROCESSES - AN AUTOTHERMAL REACTOR CASE-STUDY

A technique for the analysis of state-space linear systems is applied to the problem of selection of resilient chemical process designs. Structural Dominance Analysis affords the evaluation of many process design and control configurations and assessment of the effects of potential manipulated variables and disturbances. After a brief presentation of the analysis method, a complex multibed tubular autothermal reactor system is examined. Resilient process configurations, ease of control, and effects of various inputs on reactor state variables and outputs are considered, and effective control configurations are selected.Endnote format citatio

STABILITY OF TUBULAR AND AUTOTHERMAL PACKED-BED REACTORS USING PHASE PLANE ANALYSIS

The regions of stability and parametric sensitivity of countercurrent reactor/heat exchangers are determined explicitly in the plane of inlet feed temperature-inlet coolant temperature. The concept of phase plane analysis is generalized to include all orders of reaction rate expressions, a broader range of system parameters, and is extended to the case of autothermal reactors. An industrial hydrocarbon oxidation reactor model and an autothermal CO oxidation reactor model have been used to illustrate and to evaluate the analysis method. The approach presented here is appealing since the region of safe inlet temperatures is determined explicitly and the region of safe operation can be optimized with respect to the reactor design parameters.Endnote format citatio